Postdoctoral Fellow in Bioinformatics – Chemoproteomics & Cancer Functional Genomics

H. Lee Moffitt Cancer Center • Full-time • Tampa, FL, US • 7m ago

Postdoctoral Fellow in Bioinformatics – Chemoproteomics & Cancer Functional Genomics

Position Overview

A postdoctoral fellow position is available for a highly motivated scientist with expertise in bioinformatics, chemoproteomics, and functional genomics. The successful candidate will participate in research projects leveraging large-scale chemoproteomics datasets, integrating these with public cancer genomics resources, and mining CRISPR screening data to advance cancer biology and therapeutic discovery.

Key Responsibilities:

Analyze and integrate high-dimensional chemoproteomics datasets with multi-omotic data (e.g., genomics, transcriptomics, proteomics) from public repositories such as DepMap and TCGA
Develop, implement, and maintain robust computational pipelines in R and other programming languages (e.g., Python) for data processing, statistical analysis, and visualization
Mine and interpret large-scale CRISPR screening datasets to identify novel cancer dependencies and therapeutic targets, utilizing resources such as DepMap and published CRISPR screens
Collaborate with interdisciplinary teams of biologists, chemists, and clinicians to design and execute integrative studies, and contribute to the functional validation of computational predictions
Present research findings at internal meetings and national/international conferences; publish results in high-impact journals
Mentor junior researchers and contribute to grant writing and manuscript preparation

Required Qualifications:

PhD in Bioinformatics, Computational Biology, Cancer Biology, Genomics, or a related field is required
Demonstrated expertise in R and proficiency in other programming languages (e.g., Python)
Experience working with and mining large public cancer genomics databases, such as DepMap and TCGA
Proven track record in analyzing and integrating chemoproteomics and/or functional genomics datasets, especially CRISPR screening data
Strong understanding of statistics and machine learning concepts as applied to biological data
Excellent written and verbal communication skills, with a history of publishing in peer-reviewed journals
Ability to work independently and collaboratively in a multidisciplinary research environment

Preferred Qualifications

Experience with drug development and/or chemistry

Familiarity with AI/ML approaches for biological data analysis.

Prior experience in cancer research or translational bioinformatics

Application Instructions:

Interested applicants should submit a CV, a cover letter outlining research experience and interests, and contact information for three references. Applications will be reviewed on a rolling basis.

Location: H. Lee Moffitt Cancer Center & Research Institute · Clinical Science Lab
Schedule: Full Time, Day Shift, variable